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Automating Outbound Process for Auto Logistics

In 2017 we consulted an automotive logistics company in Mumbai on automating their vehicle inspection and outbound process. In this post we will discuss the problem and share our learnings from the engagement.

What is Automotive logistics

Auto logistics consists of inbound, in-factory and outbound logistics, with most auto manufacturers focusing on optimising the inbound process. Logistics costs for the automotive industry comprises 4.5-5.0% of their total revenue, with outbound logistics contributing the most. Currently, many aspects of outbound vehicle logistics – capacity planning and volume tracking are done using spreadsheets, emails or even faxes.

Key Trends in Outbound Logistics

Investment in IT & physical infrastructure

Multimodal transportation

Rise in 3PL participation

Intelligent Yard Management software

Vertically integrated planning (production to sales)

Blockchain for universal source of truth

The present scenario

Following is the process being followed by the auto logistics company. Each process was done manuallyThe client had identified 4 key issues in its outbound logistics management:

Solution Overview

We proposed an end-to-end outbound logistics management suite built on a custom requirements-led framework to gain higher visibility over operations, increase process efficiency and derive crucial data insights from day-to-day operations at various plant RSOs in India. This system facilitates semi-automation of the following manual processes within the outbound value chain, by reducing paperwork, eliminating human error, improving data accuracy and increasing speed and labor utilisation.

Inspection

Monitoring

Processing

Documentation

Dispatching

Reporting

The software technology solution will implement and accomplish the following:

Connect, view and extract data from hardware components on to master dashboard for collaborative cloud-based configuration and management

Geo tagging of each location where units are stored for error free tracking of vehicles

Scanning RFID tags instead of filling up reports by hand during Inspection cycle

Tracking the vehicles outward to other internal departments as well as during QC process

Key advantages

Information capturing & availability- Cross-platform and responsive system that aggregates real-time data from RFIDs at the plant, RSO and trailer dock to make information always available for stakeholders in Operations Management

Labor utilisation- Communication between the system and the operator will allow the system to pace the operator from one assigned task to the next. The system can select the next task for an operator based on metrics and instructions applied (e.g. priority queue, capability of operator, schedule of tasks, etc.) as well as on the process flow protocol configured for the task. The result is workload management that maximises task accomplishment and minimises labor idle time.

Technology- Web based open source technology solution that provides flexibility for customisation. Scalable solution that can be deployed in short time across the distribution network. Extensive use of enabling technologies (RFID, GIS & GPS features etc.) for simplified operations and real-time visibility. Fully customisable modules combining best-of-breed global industry practices fulfilling specific client requirements. Flexible architecture for easy functional upgrade and scalability to multiple sites.

Custom framework for Inspection Management

Operator mobile application & web-app

Role based hierarchical user access management – only viewable to the right person

Location intelligence based process authorisation & completion – only viewable at the right location

Mobile app to be able to scan QR/barcode pasted on the car and fetch checklist pertaining to vehicle or view previous completed activities

Manual data input management system pertaining to Inspection, Checking and Verification – can be fed into the mobile app directly. In case of errors, click a photo and upload the same. Can’t upload a saved image.

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